Seasonal climate and crop forecasts for agricultural risk management

Training related to the Climate Predictability Tool (CPT)

25–27 April 2013 at CIAT, Cali-Colombia

Rationale

The Climate Predictability Tool (CPT) is a package that facilitates the construction of seasonal climate forecast

models, investigations into model validation and producing forecasts given updated data. The CPT design has been

tailored to produce seasonal climate forecasts using model output statistic corrections to climate predictions from

general circulation models, or to produce forecasts using fields of sea-surface temperatures. Although the

software is specifically tailored for these applications, it can also be used in more general settings to perform

canonical correlation analysis or principal components regression on any data for any application.

Limited work has been done regarding the usage of crop models coupled with seasonal climate forecasts across

the Andean Region. There is a significant opportunity to reduce the production risks inherent to rainfed agriculture

in the low-input systems of the Andes by means of the timely dissemination of seasonal crop yield predictions to

farmers and government officers. When reliable climate forecasts are available, farmers may modify when, how

and what they plant accordingly and they may also use this information to decide on the type of management

practices applied to a given cropping system. This in turn should lower the production risks imposed by climate

variability and result in increased agricultural output. However, coupling crop models with seasonal climate

forecasts for farming applications is a challenging task. This is because most crop models have been developed

under optimal experimental, rather than on-farm, conditions and also because of the inherent errors and

uncertainties in both climate and crop modeling.

The project "Seasonal climate forecasts for agricultural crop and risk management" was jointly developed by the

International Center for Tropical Agriculture (CIAT) and the National Institute for Space Research (INPE), Brazil,

under the CGIAR Research Program on Climate Change, Agriculture and Food Security (CCAFS) and Colombia´s

Ministry of Agriculture and Rural Development (MADR). Within the project, we propose the development of a

methodology that combines the seasonal climate forecasts of the regional climate Eta Model, maintained by INPE,

with the Climate Predictability Tool (CPT), developed by the International Research Institute for Climate and

Society (IRI), as a starting point to produce seasonal forecasts of crop productivity. The tool is hereby proposed and

tested for operational use and for further use in climate variability studies.

Activity Description

One of the focal activities carried out under the project is the training course “Seasonal climate forecast, using the

CPT: Statistical methods and forecast quality” to be held at CIAT headquarters in Cali, Colombia, 25–27 April. The

participating institutions include: the International Potato Center (CIP); the Institute of Hydrology, Meteorology

and Environmental Studies (IDEAM), Colombia; MADR, INPE, and CIAT. The objectives of the training are to:

1. Provide a complete introduction to and training in the use of the Climate Predictability Tool (CPT), given

by an IRI scientist. Followed by discussions on the use of the CPT in crop yield forecasting, procedures to

combine the CPT with other outputs and possible strategies for improving seasonal prediction quality.

2. Establish the necessary inter-institutional links to facilitate collaboration on the application of seasonal

climate forecasts on agricultural risk management.

3. Construct methodology to apply seasonal climate forecasts with the CPT to improve agricultural yield

forecasting.

Speakers

Anthony Barnston. Prior to arriving to IRI at the end of June 2000, Barnston was an

operational seasonal climate forecaster and developmental researcher in empirical

prediction methodology at the Climate Prediction Center of the National Oceanic and

Atmospheric Administration (NOAA), USA, for 17 years. He has authored atlases, reports, and

journal papers on weather and climate, many of which are about statistical diagnoses of

large-scale circulation patterns and on empirical climate prediction. He was editor of the

Experimental Long Lead Forecast Bulletin from 1992 to 1997. Barnston has received awards

from the Department of Commerce and the American Meteorological Society.

Participants

Angélica Giarolla. PhD in Agricultural Engineering from the State University of Campinas,

Brazil. With experience in agro-meteorology, crop modeling, climatic risk in agriculture,

weather forecast for agriculture and climate change. She is currently working at the Center

for Earth System Science, National Institute for Space Research (CCST/INPE), Brazil.

Néstor Hernández Iglesias. MSc in Physical Oceanography, from the University of Gdańsk,

Poland. He has great professional experience, with positions in both public and private

sectors, where he has been able to demonstrate and utilize his know-how in diverse topics,

such as technological development in agriculture, research, innovation and technology

transfer, food security, international relationships and trade, with special emphasis in

climate change, weather variability, and environmental sustainability of agricultural projects.

Since 2008, he has worked for Colombiaʼs Ministry of Agriculture and Rural Development.

Valesca Rodriguez Fernandes. MSc in Meteorology from the Federal University of Alagoas.

Experienced in agro-meteorology and atmospheric modeling, Valesca is currently working at

the Center for Weather Forecast and Climate Studies, National Institute for Space Research

(CPTEC/INPE), Brazil.

José Francisco Boshell. MSc in Agricultural Meteorology, University of Nebraska, USA. Expert

in Agricultural Meteorology at the World Meteorological Organization (Uruguay, Honduras,

Guatemala, Colombia). Consultant in Agricultural Climatology at Colombiaʼs National

Planning Department (DNP); Colombian Corporation for Agricultural Research (CORPOICA);

International Center for Tropical Agriculture (CIAT); German Agency for International

Cooperation (GIZ); Food and Agriculture Organization of the United Nations (FAO);

International Center for El Niño Event Research (CIIFEN). Associate Professor at the National

University of Colombia (UNAL). Technical Secretary of the Inter-Institutional Network for

Climate Change and Food Security (RICCLISA).

Felipe de Mendiburu. A statistician who worked as a researcher at the International Potato

Center (CIP) from 1994 to 2012, with a masters degree in Systems Engineering (National

Engineering University, Peru) and Certified by the American Society for Quality (ASQ), USA,

in Six Sigma Green Belt. Felipe is currently working in CIPʼs Production Systems and

Environment Sub-program. Since 1978, he is a professor in Applied Statistics, Numerical

Methods, and Computer Systems at the National Agrarian University La Molina, Peru.

Author and maintainer of the AGRICOLAE package on the R-Project since 2006.

Diana Giraldo. A Research Assistant of the International Center for Tropical Agriculture

(CIAT) and the International Potato Center (CIP), with an MSc in Meteorology from the

National Agrarian University La Molina, Peru, with a special focus in using seasonal climate

forecasts in Latin America. She brings her knowledge and experience in agro-climatic

models, climate change scenarios, coupling crop models with seasonal climate forecasts and

adaptation/mitigation strategies to quantify potential climate impacts.

Gloria Leoón. A meteorologist with strong experience in observational and climatological

studies, weather forecasting, and climate prediction. Knowledgeable in numerical weather

prediction (NWP), climate models, and radiation models. Professional in interdisciplinary

projects for implementation, operation, and analysis of numerical models, such as WRF,

MM5, CAM, TUV, and development of statistical models for seasonal climate prediction in

Colombia. Consultant to the Institute of Hydrology, Meteorology and Environmental Studies

(IDEAM) and International Center for Tropical Agriculture (CIAT)

Carlos Navarro. A Research Assistant of CIATʼs Decision and Policy Analysis (DAPA) Research

Area. He graduated as an Agricultural Engineer from the National University of Colombia. He

has 2 years experience working at CIAT and his research has focused on climate modeling,

global climate models validation, generation of regional future climate scenarios and

downscaling techniques, necessary for assessing the impacts of climate change on

agriculture and planning adaptive strategies on crops.

David Arango. A statistician with experience in processing data for statistical modeling

studies, sampling, and spatial analysis. David currently works in CIATʼs DAPA Research Area.

Qualified in georeferenced data management and analysis using the statistical software R.

David is working on the Climate Analogues project, a tool to support the planning and

adaptation of agriculture to climate change through the identification of areas that have

similar climate conditions to the current or future climate of a reference site.

Camilo Barrios. An Agricultural Engineer from the University of Valle, Colombia, with

experience in climate impact studies on the development and productivity of agricultural

crops. With expertise in agro-meteorology, crop modeling, and global climate models,

analysis of the impact of climate variability and change on agriculture, and knowledge in

systems programming and statistical programs for mathematical and statistical analysis.

Camilo currently works in CIATʼs DAPA Research Area, on climate and crop modeling.

Martha Cadena. MSc in Meteorology from the National University of Colombia. She

currently works with the Climatology Group of IDEAMʼs Meteorology Division. She is in

charge of the Marine Meteorology Program and has carried out studies on marine

climatology, tide forecast models, and adaptation of international models for surge and

wind forecast in the Colombian marine zones. In the Agro-meteorology program, she

works in climate risk posed by the ENSO Phenomenon (also known as El Niño).

Juan Arciniegas. Economist with a specialization in Local and Regional Development. He

currently work with the Ministry of Agriculture and Rural Development. Preparation and

review of economic situation bulletins and agricultural sector analysis. Review and

validation of the agricultural statistics in order to elaborate the analysis of the agricultural

sector. Support in preparation of the Agro-Industrial Satellite Account for the National

Accounts.Suport in preparation of the Statistical Sectoral Plan 2012-2015 for agricultural,

stockbreeding, forestry and aquaculture.

Alejandro Ruiz. Agricultural Engineering from the National University of Colombia,

working life in 2004 on a flower farm in the production area, irrigation and fertilization, in

2007 to work in a crop wine company called “Kendall Jackson Wines in California”, I

learned agriculture technology management and development of crops, then work in the

states of Iowa, Minnesota, Nebraska in a company called “Midwest Independent Soil

Sampling” they provides services in the area of precision agriculture for corn, soybeans

and alfalfa, there I gained knowledge in this area such as management of soil, water,

climate and production, focusing on the decision-making of producers.

Notes and observations

Edward Jones. A visiting researcher for CIATʼs DAPA Research Area. Edward recently

graduated with a Bachelor of Science in Agriculture (Hons I) from the University of

Sydney, Australia. Specializing in soil science, he completed a research thesis

investigating how the surface properties of soil minerals affect the amount and

composition of organic matter bound to the mineral surface. Edward is currently

working on further development of the Climate Analogues tool with a specific focus of

incorporating soil data into the model to increase the agronomic applicability of the tool.

Location and logistics

CIAT is located near Palmira, Department of Valle del Cauca,

Colombia, on a beautifully landscaped 522-hectare campus, home

to a rich array of native and exotic trees and plants and haven to

a myriad of birds. Our headquarters offers a variety of services

and amenities for the convenience of the Center’s staff and

visitors. Whether you plan to participate in an event hosted at

CIAT or visit the Center for a few days, we invite you to take a 3-D

virtual tour of our Guest House and Conference Area facilities.

http://ciat.cgiar.org/visiting-ciat/

Program

Thursday, 25 April 2013

Time Session

8:00 – 10:00am Quimbaya room

Welcome and introduction

By Andy Jarvis, Director of CIATʼs Decision and Policy Analysis (DAPA) Research Area

Speakers: (15 minutes)

1. IRI Seasonal Climate Forecasts by Anthony Barnston – International Research Institute for Climate and Society (IRI)

2. Cropwat: a further review by Francisco Boshell – Consultant to the International Center for Tropical Agriculture (CIAT) and Professor at the National University of Colombia (UNAL)

3. Eta model - Application in agricultural sector by Angélica Giarolla– The Earth System Science Center, National Institute for Space Research (CCST/INPE), Brazil

4. Predictability of seasonal precipitation over Colombia by Gloria León

– Consultant to the International Center for Tropical Agriculture (CIAT)

5. Agricolae – a free statistical library for agricultural research by Felipe de Mendiburu – The International Potato Center (CIP)

6. Ecuatorialidad and tropicality concepts by Néstor Hernández – Colombiaʼs Ministry of Agriculture and Rural Development (MADR)

7. Climate risk - ENSO Phenomenon by Martha Cadena – Institute of Hydrology, Meteorology and Environmental Studies (IDEAM), Colombia

10:00 – 10:15 am BREAK

10:15 – 11:00 am Tolima room

Training goals and logistics - Diana Giraldo Introducing the Climate Predictability Tool (CPT) - Tony Barnston, IRI Group Dynamics: getting to know each other - Brief participant introductions 5 minutes each (introduce yourself )

11:00 – 12:00 m Tolima room

Scientific basis for seasonal climate prediction: Mechanisms through which SST anomalies can tilt the odds for specific climate anomalies, and associated agricultural effects

12:00 – 1:00 pm Tolima room

Introduction to IRI Data Library Organization of data archives Selection of desired subsets of large data sets Downloading data in desired format

1:00 – 2:00 pm

Lunch

2:00 – 5:00 pm Tolima room

Using the Climate Predictability Tool (CPT) for agricultural predictions Introduction to how the CPT works: The CCA method, predictor (climate) data and predictand (e.g., crop yield) data; model building Choice of statistical (observational) forecast design or dynamical model forecast design Examples of data input to the CPT, running the CPT, and interpreting the results 1. Preparing the CPT parameters 2. Running the CPT 3. Assessing skill levels: Verification measures, and what they tell us

Friday, 26 April 2013 – Tolima room

Time Session

8:00 – 10:00 am Using the Climate Predictability Tool (CPT) for agricultural predictions (cont.) More on interpreting results: 1. Assessing skill levels 2. Understanding EOF and CCA modes; what the patterns mean

10:00 – 10:15 am BREAK

10:15 – 1:00 pm Using the Climate Predictability Tool (CPT) for agricultural predictions (cont.) More on interpreting results: 1. Understanding probability forecasts and their relationships to signal and

skill 2. Making real-time forecasts

1:00 – 2:00 pm Lunch

2:00 – 5:00 pm Using the Climate Predictability Tool (CPT) for agricultural predictions (cont.) 1. Designing appropriate predictors and predictands for specific agricultural

forecast problems 2. Selecting initial predictor and predictand domains, best predictor-

predictand time lag 3. Iterating and optimizing predictor-predictand design for predictive skill

Saturday, 27 April 2013

Time Session

9:00 – 10:00 am

Practice in finding best predictors for agricultural predictions in region(s) Using logical approaches to individual prediction problems: Trainees develop own schemes

10:00 – 10:15 am BREAK

10:15 – 1:00 pm Practice in finding best predictors for agricultural predictions in region(s) Using logical approaches to individual prediction problems: Trainees develop own schemes

1:00 – 2:00 pm Lunch

2:00 – 5:00 pm Presentations of individual prediction schemes and results by trainees Discussion of findings, suggestions on further improvements